雾计算中不同架构的比较

Vasileios Karagiannis, Stefan Schulte
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引用次数: 24

摘要

随着雾计算的普及,人们提出了各种分布式架构来将云扩展到网络的边缘。然而,到目前为止,还没有研究比较不同的雾计算架构,并产生定量的结果,以检查每个架构在不同用例中的效率。这样的研究可以为雾计算选择合适的分布式架构提供指导,同时考虑到最终应用程序的需求。为了弥合文献中的这一差距,我们创建了一个统一的系统模型,该模型能够表示雾计算常用的基本架构,即分层和平面。此外,我们设计了可用于创建遵循这些架构的雾计算系统的算法,并且我们执行了各种专注于通信延迟和带宽利用率的实验。值得注意的是,我们的结果表明,对于不依赖于云的应用程序,即不涉及资源要求高的任务,与平面相比,分层架构减少了13%的通信延迟。然而,对于还包含资源要求较高的任务的应用程序,与分层结构相比,扁平架构减少了16%的通信延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Alternative Architectures in Fog Computing
Since the proliferation of fog computing, various distributed architectures have been proposed to extend the cloud to the edge of the network. However, so far there exists no study that compares different fog computing architectures, and produces quantitative results in order to examine the efficiency of each architecture for different use cases. Such a study could provide guidelines for selecting an appropriate distributed architecture for fog computing while taking into account the requirements of the final applications.To bridge this gap in the literature, we create a unified system model which is able to represent the basic architectures commonly used for fog computing, i.e., hierarchical and flat. Furthermore, we design algorithms that can be used for creating fog computing systems that follow these architectures, and we perform various experiments that focus on communication latency and bandwidth utilization. Notably, our results show that for applications that do not have a dependency on the cloud, i.e., no resource-demanding tasks are involved, the hierarchical architecture reduces the communication latency by 13% compared to the flat. However, for applications that also include resource-demanding tasks, the flat architecture reduces the communication latency by 16% compared to the hierarchical.
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